• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.403-410
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• 1998

An immune system has powerful abilities such as memory recognition and learning how to respond to invading antigens, and has been applied to many engineering algorithms in recent year. In this paper, the combined optimization algorithm (Immune-Genetic Algorithm: IGA) is proposed for multi-optimization problems by introduction the capability of the immune system that controls the proliferation of clones to the genetic algorithm. The new combined algorithm is applied to minimize the total weight of the rotor shaft and the transmitted forces at the bearings in order to demonstrate the merit of the combined algorithm. The inner diameter of the shaft and the bearing stiffness are chosen as the design variables. the results show that the combined algorithm can reduce both the weight of the shaft and the transmitted forces at the bearing with dynamic constraints.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.1-20
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• 2018

Service composition in the Inter-Cloud raises new challenges that are caused by the different Quality of Service (QoS) requirements of the users, which are served by different geo-distributed Cloud providers. This paper aims to explore how to select and compose such services while considering how to reach high efficiency on cost and response time, low network latency, and high reliability across multiple Cloud providers. A new hybrid multi-objective evolutionary algorithm to perform the above task called LS-NSGA-II-DE is proposed, in which the differential evolution (DE) algorithm uses the adaptive mutation operator and crossover operator to replace the those of the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) to get the better convergence and diversity. At the same time, a Local Search (LS) method is performed for the Non-dominated solution set F{1} in each generation to improve the distribution of the F{1}. The simulation results show that our proposed algorithm performs well in terms of the solution distribution and convergence, and in addition, the optimality ability and scalability are better compared with those of the other algorithms.

• 융합신호처리학회논문지
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• 제9권1호
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• pp.39-45
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• 2008

WDM 네트워크는 높은 전송속도와 낮은 지연시간으로 메트로폴리탄 네트워크뿐만 아니라 최근 기가비트 이더넷 등을 이용하여 근거리 망에서도 많은 연구가 진행되어 왔다. 네트워크의 성능은 네트워크 구조의 파라미터 값들과 사용되는 Medium Access Control 프로토콜의 파라미터 값들에 많이 의존한다. 또한 네트워크 효율성과 지연시간은 주로 상반된 관계를 보여 한쪽의 희생이 불가피 하였다. 네트워크를 효율적으로 운용하기 위해서는 효율성과 지연시간이라는 성능의 최적값을 찾아야 상황에 맞게 운용할 수 있다. 본 논문에서는 Arrayed Waveguide Grating (AWG) 기반의 성형 WDM 네트워크상에서 효율성의 최대화와 지연시간의 최소화라는 두 개의 서로 상반된 목적 함수를 유전자 알고리즘 기반의 방법론을 이용하여 파레토 최적화 곡선이라는 최적의 값들을 찾아내었다. 이를 이용하여 구한 최적의 네트워크 구성을 위한 파라미터 값들과 MAC 프로토콜의 파라미터 값들을 이용하여 상황에 따른 최적의 네트워크 성능을 유추할 수 있게 되었다. 본 논문에 사용된 유전자 알고리즘을 이용한 최적화 방법은 이와 유사한 상반된 목적 함수를 갖는 네트워크의 성능을 최적화하는데 사용필 수 있을 것이다.

• 한국안전학회지
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• 제33권2호
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• pp.61-67
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• 2018

This study proposes a new vibration control approach for adjacent twin structures, which is termed as viscous damper asymmetric coupling system in this paper. The proposed system takes a concept that the diagonal bracing viscous dampers are asymmetrically distributed in two buildings to break the behavior symmetry of the twin buildings and then the coupling viscous damper is additionally installed at the top floor of the two buildings to couple both buildings and interactively transfer the asymmetric behavior-caused damping forces into both buildings. These asymmetric damping distributions and interacting damping forces of the connection damper efficiently suppress the overall vibration of the damper-coupled adjacent twin buildings efficiently. Genetic algorithm (GA) based multi-objective optimization technique is adopted for optimal design of the proposed system. In the numerical example of adjacent twin 10-story building structures, the conventional control approach, that is, uniform damping distribution system (UDS) is also taken into account for comparison purpose. The optimization results verify that the proposed system either can improve the control performance over the UDS with the same damping capacity, or can save the damping capacity significantly while maintaining the similar level of control performance to the UDS.

• Geomechanics and Engineering
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• 제10권6호
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• pp.709-726
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• 2016

Corrugated-core sandwich panels are prevalent for many applications in industries. The researches performed with the aim of optimization of such structures in the literature have considered a deterministic approach. However, it is believed that deterministic optimum points may lead to high-risk designs instead of optimum ones. In this paper, an effort has been made to provide a reliable and robust design of corrugated-core sandwich structures through stochastic and probabilistic multi-objective optimization approach. The optimization is performed using a coupling between genetic algorithm (GA), Monte Carlo simulation (MCS) and finite element method (FEM). To this aim, Prob. Design module in ANSYS is employed and using a coupling between optimization codes in MATLAB and ANSYS, a connection has been made between numerical results and optimization process. Results in both cases of deterministic and probabilistic multi-objective optimizations are illustrated and compared together to gain a better understanding of the best sandwich panel design by taking into account reliability and robustness. Comparison of results with a similar deterministic optimization study demonstrated better reliability and robustness of optimum point of this study.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2005년도 학술발표회(2)
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• pp.1224-1225
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• 2005

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권7호
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• pp.1671-1689
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• 2013

The key issue of block-based multi-focus image fusion is to determine the size of the sub-block because different sizes of the sub-block will lead to different fusion effects. To solve this problem, this paper presents a novel genetic algorithm (GA) based multi-focus image fusion method, in which the block size can be automatically found. In our method, the Sum-modified-Laplacian (SML) is selected as an evaluation criterion to measure the clarity of the image sub-block, and the edge information retention is employed to calculate the fitness of each individual. Then, through the selection, crossover and mutation procedures of the GA, we can obtain the optimal solution for the sub-block, which is finally used to fuse the images. Experimental results show that the proposed method outperforms the traditional methods, including the average, gradient pyramid, discrete wavelet transform (DWT), shift invariant DWT (SIDWT) and two existing GA-based methods in terms of both the visual subjective evaluation and the objective evaluation.

• 상하수도학회지
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• 제29권3호
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• pp.293-303
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• 2015

Optimal design of the water supply pipe network aims to minimize construction cost while satisfying the required hydraulic constraints such as the minimum and maximum pressures, and velocity. Since considering one single design factor (i.e., cost) is very vulnerable for including future conditions and cannot satisfy operator's needs, various design factors should be considered. Hence, this study presents three kinds of design factors (i.e., minimizing construction cost, maximizing reliability, and surplus head) to perform multi-objective optimization design. Harmony Search (HS) Algorithm is used as an optimization technique. As well-known benchmark networks, Hanoi network and Gyeonggi-do P city real world network are used to verify the applicability of the proposed model. In addition, the proposed multi-objective model is also applied to a real water distribution networks and the optimization results were statistically analyzed. The results of the optimal design for the benchmark and real networks indicated much better performance compared to those of existing designs and the other approach (i.e., Genetic Algorithm) in terms of cost and reliability, cost, and surplus head. As a result, this study is expected to contribute for the efficient design of water distribution networks.

• 한국수자원학회논문집
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• 제38권10호
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• pp.861-869
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• 2005

강우-유출모형은 적용대상 유역이 가지고 있는 수문학적 성질을 최대한 반영할 수 있도록 보정되어야 한다. 본 연구에서는 SSARR 모형의 5개의 매개변수를 안동댐 상류유역에 보정하기 위하여 다중목적함수와 유전자알고리즘을 이용하였다. 다중목적함수의 최적해는 단일한 매개변수로 이루어지는 것이 아니라 다양한 목적함수들에 따라서 결정되는 파레토 최적해로 구성된다. 다중목적함수를 이용한 모형의 보정방법은 보정시간 및 작업 반복에 따른 노력을 감소시킬 수 있었으며, 파레토 최적해를 사용함으로써 적용 목적에 따라 최대유랑을 잘 모의할 필요가 있다거나 전체 체적을 잘 모의할 필요가 있는 경우에 적합한 매개변수를 사용자가 선택하여 사용할 수 있는 장점이 있다.

• 한국통신학회논문지
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• 제32권3C호
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• pp.314-322
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• 2007

본 논문에서는 CR(Cognitive Radio)을 위해 사용자에게 최적의 통신 시스템 구성 변수들을 할당하기 위한 새로운 최적화 알고리즘인 GBNSGA(Goal-Pareto Based Non-dominated Sorting Genetic Algorithm)를 제안한다. 다중모드 선택적 CR 통신을 위해 사용되는 cognitive 엔진은 Mitola가 제안한 cognition 싸이클의 많은 논리 연산과정이 필요하다는 단점을 보완하기 위하여 일반적으로 유전자 알고리즘 기반의 접근 방식이 사용되고 있다. 본 논문에서는 cognitive 엔진의 효율적인 구동을 위하여 파레토(Pareto) 기반의 최적화 알고리즘인 NSGA(Non-dominated Sorting Genetic Algorithm)와 사용자 서비스의 요구사항을 goal로 설정하는 GP(Goal Programming)을 결합한 새로운 최적화 방법으로 GBNSGA를 제안하였으며, 시뮬레이션 수행을 통해 제안된 알고리즘이 요구사항에 적합한 다양한 해를 제공하고 최적화 수렴속도가 빠르다는 것을 확인하였다.